A common form of this failure is the model picking up on random wordings from earlier in the session (e.g. some comment it made to me in the middle of a response, that I never explicitly endorsed) and then treating these as hard commitments. Or over-interpreting a specific word choice or clumsy phrasing as if it were a "load-bearing" constraint on the task.
None of this clumsiness would be so problematic if the model didn't have such a strong drive toward autonomy. It's much like with people: there's no shame in not understanding what you're being asked to do, provided you ask clarifying questions. There's no shame in ignorance if it's wedded to curiosity. Benchmaxing has RLVRed curiosity and clarification straight out of these models. It sucks.